//! # 性能监控核心实现
//! 
//! 本模块提供了RustCloud框架的性能监控核心实现。

use crate::performance_monitor::traits::*;
use rustcloud_core::{ServiceResult, ServiceError};
use std::sync::Arc;
use std::time::{Duration, Instant};
use tokio::sync::RwLock;
use tracing::{info, error};

/// 性能监控器
pub struct PerformanceMonitor {
    /// 配置
    config: PerformanceMonitorConfig,
    /// 历史指标数据
    metrics_history: Arc<RwLock<Vec<SystemMetrics>>>,
    /// 当前指标
    current_metrics: Arc<RwLock<Option<SystemMetrics>>>,
    /// 警报历史
    alert_history: Arc<RwLock<Vec<PerformanceAlert>>>,
    /// 监控开始时间
    start_time: Instant,
    /// 是否正在运行
    is_running: Arc<RwLock<bool>>,
}

impl PerformanceMonitor {
    /// 创建性能监控器
    pub fn new(config: PerformanceMonitorConfig) -> Self {
        Self {
            config,
            metrics_history: Arc::new(RwLock::new(Vec::new())),
            current_metrics: Arc::new(RwLock::new(None)),
            alert_history: Arc::new(RwLock::new(Vec::new())),
            start_time: Instant::now(),
            is_running: Arc::new(RwLock::new(false)),
        }
    }

    /// 收集系统指标（模拟实现）
    async fn collect_system_metrics() -> ServiceResult<SystemMetrics> {
        let timestamp = std::time::SystemTime::now()
            .duration_since(std::time::UNIX_EPOCH)
            .unwrap()
            .as_secs();

        // 模拟CPU使用率
        let cpu_usage = 0.1 + (timestamp % 100) as f64 / 200.0;

        // 模拟内存使用
        let total_memory = 8 * 1024 * 1024 * 1024; // 8GB
        let used_memory = (total_memory as f64 * (0.3 + cpu_usage * 0.5)) as u64;
        let available_memory = total_memory - used_memory;
        let usage_percent = used_memory as f64 / total_memory as f64;

        // 模拟网络统计
        let network = NetworkMetrics {
            bytes_received: timestamp * 1024,
            bytes_sent: timestamp * 512,
            packets_received: timestamp * 10,
            packets_sent: timestamp * 8,
            errors: 0,
            active_connections: 50,
        };

        // 模拟进程统计
        let process = ProcessMetrics {
            pid: std::process::id(),
            cpu_usage,
            memory_usage: used_memory / 10, // 进程使用系统内存的1/10
            thread_count: 20,
            fd_count: 100,
            uptime: timestamp - 1000000, // 假设进程运行了一段时间
        };

        Ok(SystemMetrics {
            cpu_usage,
            memory: MemoryMetrics {
                total: total_memory,
                used: used_memory,
                available: available_memory,
                usage_percent,
                heap_used: used_memory / 5,
                heap_total: used_memory / 3,
            },
            network,
            process,
            timestamp,
        })
    }

    /// 检查性能阈值
    fn check_thresholds(metrics: &SystemMetrics, thresholds: &PerformanceThresholds) -> Option<PerformanceAlert> {
        // 检查CPU使用率
        if metrics.cpu_usage > thresholds.cpu_critical_threshold {
            return Some(PerformanceAlert {
                level: AlertLevel::Critical,
                alert_type: "CPU_HIGH".to_string(),
                message: format!("CPU使用率过高: {:.1}%", metrics.cpu_usage * 100.0),
                current_value: metrics.cpu_usage,
                threshold: thresholds.cpu_critical_threshold,
                timestamp: metrics.timestamp,
                metrics: metrics.clone(),
            });
        } else if metrics.cpu_usage > thresholds.cpu_warning_threshold {
            return Some(PerformanceAlert {
                level: AlertLevel::Warning,
                alert_type: "CPU_WARNING".to_string(),
                message: format!("CPU使用率较高: {:.1}%", metrics.cpu_usage * 100.0),
                current_value: metrics.cpu_usage,
                threshold: thresholds.cpu_warning_threshold,
                timestamp: metrics.timestamp,
                metrics: metrics.clone(),
            });
        }

        // 检查内存使用率
        if metrics.memory.usage_percent > thresholds.memory_critical_threshold {
            return Some(PerformanceAlert {
                level: AlertLevel::Critical,
                alert_type: "MEMORY_HIGH".to_string(),
                message: format!("内存使用率过高: {:.1}%", metrics.memory.usage_percent * 100.0),
                current_value: metrics.memory.usage_percent,
                threshold: thresholds.memory_critical_threshold,
                timestamp: metrics.timestamp,
                metrics: metrics.clone(),
            });
        } else if metrics.memory.usage_percent > thresholds.memory_warning_threshold {
            return Some(PerformanceAlert {
                level: AlertLevel::Warning,
                alert_type: "MEMORY_WARNING".to_string(),
                message: format!("内存使用率较高: {:.1}%", metrics.memory.usage_percent * 100.0),
                current_value: metrics.memory.usage_percent,
                threshold: thresholds.memory_warning_threshold,
                timestamp: metrics.timestamp,
                metrics: metrics.clone(),
            });
        }

        None
    }
}

#[async_trait::async_trait]
impl PerformanceMonitorTrait for PerformanceMonitor {
    /// 启动性能监控
    async fn start(&self) -> ServiceResult<()> {
        {
            let mut running = self.is_running.write().await;
            if *running {
                return Err(ServiceError::InternalError("性能监控器已在运行".to_string()));
            }
            *running = true;
        }

        let metrics_history = self.metrics_history.clone();
        let current_metrics = self.current_metrics.clone();
        let alert_history = self.alert_history.clone();
        let config = self.config.clone();
        let is_running = self.is_running.clone();

        tokio::spawn(async move {
            let mut interval = tokio::time::interval(config.collection_interval);
            
            while *is_running.read().await {
                interval.tick().await;
                
                match Self::collect_system_metrics().await {
                    Ok(metrics) => {
                        // 更新当前指标
                        {
                            let mut current = current_metrics.write().await;
                            *current = Some(metrics.clone());
                        }

                        // 添加到历史记录
                        {
                            let mut history = metrics_history.write().await;
                            history.push(metrics.clone());
                            
                            // 清理过期数据
                            let cutoff_time = std::time::SystemTime::now()
                                .duration_since(std::time::UNIX_EPOCH)
                                .unwrap()
                                .as_secs() - config.retention_period.as_secs();
                            
                            history.retain(|m| m.timestamp > cutoff_time);
                        }

                        // 检查警报
                        if let Some(alert) = Self::check_thresholds(&metrics, &config.thresholds) {
                            let mut alerts = alert_history.write().await;
                            alerts.push(alert.clone());
                            
                            tracing::warn!("性能警报: {} - {}", alert.alert_type, alert.message);
                        }
                    }
                    Err(e) => {
                        tracing::error!("收集系统指标失败: {}", e);
                    }
                }
            }
        });

        tracing::info!("性能监控器已启动");
        Ok(())
    }

    /// 停止性能监控
    async fn stop(&self) -> ServiceResult<()> {
        let mut running = self.is_running.write().await;
        *running = false;
        
        tracing::info!("性能监控器已停止");
        Ok(())
    }

    /// 获取当前系统指标
    async fn get_current_metrics(&self) -> Option<SystemMetrics> {
        self.current_metrics.read().await.clone()
    }

    /// 获取历史指标
    async fn get_metrics_history(&self, limit: Option<usize>) -> Vec<SystemMetrics> {
        let history = self.metrics_history.read().await;
        if let Some(limit) = limit {
            history.iter().rev().take(limit).cloned().collect()
        } else {
            history.clone()
        }
    }

    /// 获取警报历史
    async fn get_alert_history(&self, limit: Option<usize>) -> Vec<PerformanceAlert> {
        let alerts = self.alert_history.read().await;
        if let Some(limit) = limit {
            alerts.iter().rev().take(limit).cloned().collect()
        } else {
            alerts.clone()
        }
    }

    /// 获取性能摘要
    async fn get_performance_summary(&self) -> PerformanceSummary {
        let history = self.metrics_history.read().await;
        let alerts = self.alert_history.read().await;
        
        if history.is_empty() {
            return PerformanceSummary::default();
        }

        let mut cpu_sum = 0.0;
        let mut memory_sum = 0.0;
        let mut max_cpu = 0.0;
        let mut max_memory = 0.0;

        for metrics in history.iter() {
            cpu_sum += metrics.cpu_usage;
            memory_sum += metrics.memory.usage_percent;
            max_cpu = max_cpu.max(metrics.cpu_usage);
            max_memory = max_memory.max(metrics.memory.usage_percent);
        }

        let count = history.len() as f64;
        
        PerformanceSummary {
            uptime_seconds: self.start_time.elapsed().as_secs(),
            avg_cpu_usage: cpu_sum / count,
            max_cpu_usage: max_cpu,
            avg_memory_usage: memory_sum / count,
            max_memory_usage: max_memory,
            total_alerts: alerts.len(),
            warning_alerts: alerts.iter().filter(|a| a.level == AlertLevel::Warning).count(),
            critical_alerts: alerts.iter().filter(|a| a.level == AlertLevel::Critical).count(),
            data_points: history.len(),
        }
    }
}